Prospects of a mathematical theory of human behavior in complex man-machine systems tasks

A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued

Human Arm simulation for interactive constrained environment design

During the conceptual and prototype design stage of an industrial product, it is crucial to take assembly/disassembly and maintenance operations in advance. A well-designed system should enable relatively easy access of operating manipulators in the constrained environment and reduce musculoskeletal disorder risks for those manual handling operations. Trajectory planning comes up as an important issue for those assembly and maintenance operations under a constrained environment, since it determines the accessibility and the other ergonomics issues, such as muscle effort and its related fatigue. In this paper, a customer-oriented interactive approach is proposed to partially solve ergonomic related issues encountered during the design stage under a constrained system for the operator's convenience. Based on a single objective optimization method, trajectory planning for different operators could be generated automatically. Meanwhile, a motion capture based method assists the operator to guide the trajectory planning interactively when either a local minimum is encountered within the single objective optimization or the operator prefers guiding the virtual human manually. Besides that, a physical engine is integrated into this approach to provide physically realistic simulation in real time manner, so that collision free path and related dynamic information could be computed to determine further muscle fatigue and accessibility of a product designComment: International Journal on Interactive Design and Manufacturing (IJIDeM) (2012) 1-12. arXiv admin note: substantial text overlap with arXiv:1012.432

Human System Engineering Applications from Distracted Driving Simulations

Most of the studies to explore the impact of distracted driving have been descriptive in nature; i.e. the research is conducted in naturalistic settings to evaluate the performance of the driver with and without distracters. However simulation models can also be used that predict the workload for driving tasks. Using concepts from process modeling, baseline models of driving tasks can be created for different driving sequences that include the associated fine motor, visual and cognitive human resources. These models can then be used to evaluate incidents of workload overload caused by different distracters, from both the internal and external vehicle environment. Identifying specific overloaded resources can lead to mitigation strategies to reduce workload and minimize distracted driving. Lessons learned from distracted driving research can then be applied to evaluation other types of manual, visual, and cognitive intensive tasks. Identifying combinations of tasks that contribute to peak workload of operators, and then simulating the impact of multi-tasking using personal devices (i.e. cell phones) can lead to management insights for other types of work environments. Additionally, iterative modeling can also include the impact of sensors and alerts, as well as enhanced workstation displays. Individual component overload can help understand causes for performance detriments during different task sequences, and the impact of additional types of technologies and activities. Using the simulation analysis, the impact on overall workload, identification of peak workload occurrences, and specific overloaded resources can lead to mitigation strategies to reduce workload and improve operator performance

Quantum field inspired model of decision making: Asymptotic stabilization of belief state via interaction with surrounding mental environment

This paper is devoted to justification of the quantum-like model of the process of decision making based on theory of open quantum systems: decision making as decoher- ence. This process is modeled as interaction of a decision maker, Alice, with a mental (information) environment R surrounding her. Such an interaction generates “dissipation of uncertainty” from Alice’s belief-state ρ ( t ) into R and asymptotic stabilization of ρ ( t ) to a steady belief-state. The latter is treated as the decision state. Mathematically the problem under study is about finding constraints on R guaranteeing such stabilization. We found a partial solution of this problem (in the form of sufficient conditions). We present the corresponding decision making analysis for one class of mental environments, so-called “almost homogeneous environments”, with the illustrative examples: a) behavior of electorate interacting with the mass-media “reservoir”; b) consumers’ persuasion. We also comment on other classes of mental environments